A comprehensive course equipping aspiring professionals with the essential skills to secure AI systems across their lifecycle, from development to deployment.
...
Introduction to AI Security
Unit 1: Understanding AI Security
Unit 2: Core Security Concepts
Unit 3: CIA Triad and AI
Fundamentals of Machine Learning for Security Professionals
Unit 1: Machine Learning Foundations
Unit 2: Machine Learning Models
Unit 3: Data and Model Evaluation
Adversarial Attacks: Evasion Attacks
Unit 1: Understanding Evasion Attacks
Unit 2: Gradient-Based Evasion Attacks
Unit 3: Beyond Gradient-Based Attacks & Transferability
Adversarial Attacks: Poisoning Attacks
Unit 1: Understanding Poisoning Attacks
Unit 2: Types of Poisoning Attacks
Unit 3: Implementing and Detecting Poisoning Attacks
Adversarial Attacks: Model Extraction Attacks
Unit 1: Understanding Model Extraction
Unit 2: Query-Based Extraction
Unit 3: Transfer-Based Extraction
Unit 4: Defense Strategies
Data Privacy in AI: Data Leakage
Unit 1: Understanding Data Privacy
Unit 2: Data Leakage: Forms and Examples
Unit 3: Data Leakage in AI Models
Unit 4: Preventing Data Leakage
Data Privacy in AI: Re-identification Attacks
Unit 1: Understanding Re-identification Attacks
Unit 2: Re-identification Techniques
Unit 3: Preventing Re-identification
Security Risks in AI Supply Chains and Dependencies
Unit 1: Understanding AI Supply Chain Risks
Unit 2: Specific Vulnerabilities and Attack Vectors
Unit 3: Mitigation and Best Practices
Adversarial Training
Unit 1: Understanding Adversarial Training
Unit 2: Generating Adversarial Examples for Training
Unit 3: Implementing Adversarial Training
Differential Privacy
Unit 1: Understanding Differential Privacy
Unit 2: Techniques for Implementing Differential Privacy
Unit 3: Applying Differential Privacy to AI Models
Federated Learning
Unit 1: Introduction to Federated Learning
Unit 2: Architectures and Algorithms
Unit 3: Implementation and Security
Secure Aggregation
Unit 1: Understanding Secure Aggregation
Unit 2: Techniques for Secure Aggregation
Unit 3: Implementing Secure Aggregation
Unit 4: Challenges and Limitations
Robust Model Design
Unit 1: Understanding Robustness
Unit 2: Techniques for Robustness
Unit 3: Adversarial Training Deep Dive
Unit 4: Advanced Robustness Techniques
Unit 5: Evaluation and Best Practices
Secure Data Handling
Unit 1: Introduction to Secure Data Handling
Unit 2: Best Practices for Data Collection
Unit 3: Best Practices for Data Storage
Unit 4: Best Practices for Data Processing
Unit 5: Compliance and Regulations
Secure Model Development
Unit 1: Secure Model Development Fundamentals
Unit 2: Secure Training, Validation, and Testing
Unit 3: Code Review and Security Audits
Secure Model Deployment
Unit 1: Introduction to Secure Model Deployment
Unit 2: Best Practices for Secure Model Deployment
Unit 3: Secure Deployment Techniques
Unit 4: Platform-Specific Security Considerations
Unit 5: Monitoring and Incident Response
Secure Model Monitoring
Unit 1: Introduction to Secure Model Monitoring
Unit 2: Techniques for Secure Model Monitoring
Unit 3: Implementing Secure Model Monitoring
Unit 4: Advanced Topics in Secure Model Monitoring
Emerging Threats and Vulnerabilities in AI
Unit 1: Understanding Emerging AI Threats
Unit 2: Specific Emerging Vulnerabilities
Unit 3: Mitigation and Staying Ahead
AI Security Assessment and Penetration Testing
Unit 1: Understanding AI Security Assessments
Unit 2: Penetration Testing AI Systems
Unit 3: Reporting and Remediation
Tools and Frameworks for Adversarial Attack Simulation
Unit 1: Introduction to Adversarial Attack Simulation Tools
Unit 2: Hands-on with Foolbox
Unit 3: Hands-on with ART (Adversarial Robustness Toolkit)
Unit 4: Advanced Tooling and Techniques
Unit 5: Selecting the Right Tool
Vulnerability Scanning and Security Auditing of AI Systems
Unit 1: Introduction to AI Vulnerability Scanning and Auditing
Unit 2: Tools and Techniques for Vulnerability Identification
Unit 3: Performing an AI Security Audit
Case Studies in AI Security
Unit 1: Introduction to AI Security Case Studies
Unit 2: Evasion Attack Case Studies
Unit 3: Poisoning Attack Case Studies
Unit 4: Model Extraction and Data Privacy Case Studies
Unit 5: Supply Chain and Emerging Threat Case Studies
